Hi, I'm Taimoor
💻 ☕️ 🧠 ❤️
20 | Deep Learning Learning | NLP and LLMs | Artificial Intelligence
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My Introduction
I am a passionate Computer Science undergraduate , actively pursuing a career in AI and ML. My interests span from theoretical research in AI to practical applications like NLP, LLMs, AI in Finance and reinforcement learning. With a strong foundation in mathematics, algorithms, and programming, I aim to contribute to ground breaking innovations in AI. I am committed to continuous learning, hands-on projects, and building skills. Let's connect and collaborate to shape the future of technology together!
Skills
My technical skillsData Science & AI
1+ Years XPNLP and LLMs
85%Data Analytics & Visualization
85%Frameworks & Libraries
75%DSA & Alogrithms
80%Probability & Statistics
90%Linear Algebra & Calculus
90%Programming
2+ Years XPPython
95%SQL
85%C++/C
90%Dart
75%Computing
1+ Years XPGPU & Distributed Computing
70%Google Cloud Platform
75%Front End
2+ Years XPHTML
90%CSS
80%JavaScript
75%Flutter
85%BackEnd
1+ Years XPPython - Flask, Fast API
95%MLOps
55%Databases
70%Misc
2+ Years XPGit
90%Jupyter, Colab
90%Certifications
My Certifications
Machine Learning Specialization
- Organization: Stanford and DeepLearning.AI
- Instructor: Andrew Ng
- Duration: 3 Months
- Courses: 03
- Completion Date: 9th January 2025
Natural Language Processing Specialization
- Organization:DeepLearning.AI
- Instructor: Younes Bensouda Mourri
- Duration: 3 Months
- Courses: 04
- Completion Date: 23rd March 2025
IBM Machine Learning Engineer Professional Certificate
- Organization:IBM
- Instructor: Rav Ahuja
- Duration: 3 Months
- Courses: 05
- Completion Date: 15 February 2025
Associate Data Scientist
NAVTTC Artificial Intelligence
Projects
My independent projects & contributions
AI powered Exame System (Work in Progress)
Auto-generate question papers using LLMs and grade scanned answer sheets with OCR and NLP. Enabled customizable marking schemes and semantic answer evaluation. Developed an interactive dashboard for managing exams and viewing results. Tech Stack: Python, Hugging Face, OpenCV, Tesseract OCR, Streamlit, FastAPI
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Cricket Game Prediction
Built a machine learning model to predict cricket match outcomes based on historical match data, player performance, and team statistics. Technologies: Python, scikit-learn, XGBoost, Pandas.
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